Abstract
<jats:p>Technological advancements in hydraulic fracturing and horizontal drilling have created a massive boom in crude oil and natural gas production in the United States. While these developments have succeeded in increasing domestic energy production, they have the potential to negatively impact wildlife populations and the habitats they depend on. Thus, understanding the proximate effects of energy development is imperative to conserving wildlife populations and creating effective mitigation strategies. In 2019, oil and gas production began to grow rapidly in southeast New Mexico due to the extraction of unconventional reserves in the Permian Basin, and this increased truck traffic on local highways. As a mitigation strategy for the high volumes of traffic this created in the region, a conveyor belt system was built spanning 67.6 km that moves sand from a sand mine in Texas to a receiving terminal in New Mexico to support fracking operations. We initiated a pre-post study of mule deer (Odocoileus hemionus) using a set of complementary metrics and fine-scale global positioning system (GPS) data to understand the impacts of the Kermit conveyor belt system and right-of-way construction to deer habitat selection, space use, and movement. Like previous studies of mule deer in areas with dense energy infrastructure, we detected a strong signal that deer avoided roads and oil and gas wells in the daytime. After controlling for base habitat selection covariates, we found that mule deer showed strong avoidance for the conveyor belt in the post-construction phase at the population level compared to pre- and active construction phases and a weaker avoidance response to the right-of-way development. We found that even individuals that selected to be closer to the conveyor belt relative to their home range over the study period showed fine-scale avoidance by increasing their minimum distance from the conveyor belt by an average of 555–915 m. We documented this fine-scale avoidance through our space use and distance analysis, which showed that 10% of mule deer locations were within 0.97 km and 1.43 km of the conveyor belt on average in the pre- and post-construction phases, respectively. Concurrently, we found that the proportion of high use area declined in the active and post-construction phases compared to the pre-construction phase for both features by factors of 4.8%–27.3%. We used barrier behavior analysis to examine how deer behaviorally responded to the conveyor belt and right-of-way construction as barriers to movement. Although we did not observe any changes in the frequency of normal or altered behaviors, we detected a significant effect on the number of 50-m sections of conveyor belt route that were encountered between the pre- and post-construction phases. For instance, less than a third of the wildlife crossing structures built in areas that were used by collared animals in the pre-construction phase were used post-construction, and the western portion of the belt had no encounter events after the conveyor belt was complete. We attribute this decline in encounter events to the fine-scale avoidance that deer showed toward the conveyor belt. In summary, it appears that the Kermit conveyor belt had significant negative effects on mule deer by causing deer to avoid the conveyor belt and reducing their ability to move across the landscape, further constraining deer populations in an area that has already seen substantial habitat alterations. Without future mitigation efforts, deer populations may experience declines like other areas in Intermountain West where habitat degradation has occurred from energy development. Improvements to wildlife crossing structures may help mitigate the impact of the conveyor belt, and continued monitoring of wildlife crossings and mule deer populations in response to mitigation strategies will be necessary to evaluate their efficacy.</jats:p>